**Noticed:**

- It’s easier for me to grok
*statistical significance*(**p**’s and**t**’s) from a scatterplot than*magnitude*(**β**’s). - Even though magnitude can be the most important thing, it’s “hidden” off to the left. Note to self: look off to the left more, and for longer.
- But I’m set up to understand the correlativeness in a sub_i, sub_j sense — which particular countries fit the pattern as well as how closely.

**Questions:**

- Minute __:__ Do
*each*of the dimensions of social problems correlate*individually*, or is this only a mass effect of the combination?

If it’s true that raising marginal tax rates on the rich lowers crime rates without paying for any anti-crime programmes, that’s almost a free lunch.

**UPDATE:** Oh, hey, six months after I watch this and 3 days after I put up the story, I see Harvard Business Review has a story corroborating the same effect, instead pointing out how economists don’t look at the **p**’s and **t**’s on a regression table. I feel like I “mentally cross out” any lines with a low **t** value and then wonder about the **F** value on a regression with the “worthless” line removed.

(Source: http://video.ted.com/)

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